Software Open Access
Giovanni Spitale;
Federico Germani;
Nikola Biller - Andorno
The purpose of this tool is performing NLP analysis on Telegram chats. Telegram chats can be exported as .json files from the official client, Telegram Desktop (v. 2.9.2.0).
The files are parsed, the content is used to populate a message dataframe, which is then anonymized.
The software calculates and displays the following information:
The software outputs:
Dependencies:
This code is optimized for Italian.
Lemma analysis is based on spaCy, which provides several other models for other languages ( https://spacy.io/models ) so it can easily be adapted.
Sentiment analysis is performed using FEEL-IT: Emotion and Sentiment Classification for the Italian Language (Kudos to Federico Bianchi <f.bianchi@unibocconi.it>; Debora Nozza <debora.nozza@unibocconi.it>; and Dirk Hovy <dirk.hovy@unibocconi.it>). Their work is specific for Italian. To perform sentiment analysis in other languages one could consider nltk.sentiment
The code is structured in a Jupyter-lab notebook, heavily commented for future reference.
Name | Size | |
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telegram social listening v1.0.0.zip
md5:67bb88c8016699f875c4e486470e7bfc |
5.9 MB | Download |
Bianchi F, Nozza D, Hovy D. FEEL-IT: Emotion and Sentiment Classification for the Italian Language. In: Proceedings of the 11th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis. Association for Computational Linguistics; 2021. https://github.com/MilaNLProc/feel-it
All versions | This version | |
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Views | 253 | 15 |
Downloads | 13 | 2 |
Data volume | 49.6 MB | 11.8 MB |
Unique views | 229 | 15 |
Unique downloads | 11 | 2 |